Biconvex optimization is a generalization of convex optimization where the objective function and the constraint set can be biconvex. There are methods that can find the global optimum of these proble
In mathematics, a real-valued function is called convex if the line segment between any two points on the graph of the function lies above the graph between the two points. Equivalently, a function is
In mathematics, a function is supermodular if for all , , where denotes the componentwise maximum and the componentwise minimum of and . If −f is supermodular then f is called submodular, and if the i
In mathematics, a quasiconvex function is a real-valued function defined on an interval or on a convex subset of a real vector space such that the inverse image of any set of the form is a convex set.
In mathematical optimization, linear-fractional programming (LFP) is a generalization of linear programming (LP). Whereas the objective function in a linear program is a linear function, the objective
In convex analysis and the calculus of variations, both branches of mathematics, a pseudoconvex function is a function that behaves like a convex function with respect to finding its local minima, but
In vector calculus, an invex function is a differentiable function from to for which there exists a vector valued function such that for all x and u. Invex functions were introduced by Hanson as a gen